A Damping Grid Strapdown Inertial Navigation System Based on a Kalman Filter for Ships in Polar Regions

This paper deals with the strapdown integration of attitude estimation Kalman filter (KF) based on inertial measurement unit (IMU) signals. In many low-cost wearable IMU applications, a first-order is selected for strapdown integration, which may degrade attitude estimation performance in high-speed angular motions. The purpose of this research is to provide insights into the effect of the strapdown integration order and sampling rate on the attitude estimation accuracy for low-cost IMU applications. Experimental results showed that the effect of integration order was small when the angular velocity was low and the sampling rate was large. However, as the angular velocity increased and the sampling rate decreased, the effect of integration order increased, i.e., obviously, the third-order KF resulted in better estimations than the first-order KF. When comparing the case where both transient matrix and process noise covariance matrix are applied to the corresponding order and the case where only the transient matrix is applied to the corresponding order but the process noise covariance matrix for the first-order is still used, both cases had almost equivalent estimation accuracy. However, in terms of the calculation cost, the latter case was more economical than the former, particularly for the third-order KF (i.e., the ratio of the former to the latter is 1.22 to 1).

Section: Introductionmentioning

confidence: 99%

Effect of Strapdown Integration Order and Sampling Rate on IMU-Based Attitude Estimation Accuracy

Lee

Choi

2018

“…Strapdown inertial navigation systems (SINSs) are widely used in modern navigation applications, especially in the military field because of their advantage of complete autonomy [ 1 , 2 , 3 ]. Initial alignment plays an important role in SINS, and the accuracy and efficiency of initial alignment affect the SINS capability directly [ 4 , 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

An Improved ACKF/KF Initial Alignment Method for Odometer-Aided Strapdown Inertial Navigation System

Gao

Ren

et al. 2018

For a land-vehicle strapdown inertial navigation system (SINS), the problem of initial alignment with large misalignment angle in-motion needs to be solved urgently. This paper proposes an improved ACKF/KF initial alignment method for SINS aided by odometer. The SINS error equation with large misalignment angle is established first in the form of an Euler angle. The odometer/gyroscope dead reckoning (DR) error equation is deduced, which makes the observation equation linear when the position is taken as the observation of the Kalman filter. Then, based on the cubature Kalman filter, the Sage-Husa adaptive filter and the characteristics of the observation equation, an improved ACKF/KF method is proposed, which can accomplish initial alignment well in the case of unknown measurement noise. Computer simulation results show that the performance of the proposed ACKF/KF algorithm is superior to EKF, CKF and AEKF method in accuracy and stability, and the vehicle test validates its advantages.

“…Li et al [ 23 ] proposed a polar damping technology for the transverse strapdown INS based on the system’s static error characteristics. Huang et al designed a damping algorithm based on the Kalman filter to reduce the overshoot errors due to the switch from the non-damping state to the damping state [ 24 ]. In this paper, the damping technology is discussed, and two more aspects are taken into consideration: First, outside of the polar areas, the kinematic error characteristics could be analyzed using static models, as the system’s angular velocity around the Earth’s axis is far less than the Earth’s rotational rate.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Transverse Polar Navigation for High-Precision and Long-Term INSs

Han

et al. 2018

Transverse navigation has been proposed to help inertial navigation systems (INSs) fill the gap of polar navigation ability. However, as the transverse system does not have the ability of navigate globally, a complicated switch between the transverse and the traditional algorithms is necessary when the system moves across the polar circles. To maintain the inner continuity and consistency of the core algorithm, a hybrid transverse polar navigation is proposed in this research based on a combination of Earth-fixed-frame mechanization and transverse-frame outputs. Furthermore, a thorough analysis of kinematic error characteristics, proper damping technology and corresponding long-term contributions of main error sources is conducted for the high-precision INSs. According to the analytical expressions of the long-term navigation errors in polar areas, the 24-h period symmetrical oscillation with a slowly divergent amplitude dominates the transverse horizontal position errors, and the first-order drift dominates the transverse azimuth error, which results from the g0 gyro drift coefficients that occur in corresponding directions. Simulations are conducted to validate the theoretical analysis and the deduced analytical expressions. The results show that the proposed hybrid transverse navigation can ensure the same accuracy and oscillation characteristics in polar areas as the traditional algorithm in low and mid latitude regions.